Hi @indulgeBai 馃
I'm Niels and work as part of the open-source team at Hugging Face. I discovered your work through Papers with Code as yours got featured: https://paperswithcode.co/paper/2606.17800.
The paper page lets people discuss about your paper and lets them find artifacts about it (your models for instance), you can also claim the paper as yours which will show up on your public profile at HF, add Github and project page URLs.
It's great to see that you've already set up the model repository for MaineCoon on the Hub!
Would you also like to host the SocialVideo-Bench dataset you've introduced on https://huggingface.co/datasets?
Hosting the benchmark on Hugging Face will give it more visibility and enable better discoverability within the research community. It will also allow people to easily use the benchmark via the library:
from datasets import load_dataset
dataset = load_dataset("catnip-ai-tech/SocialVideo-Bench")If you're interested, you can find a guide for uploading datasets here: https://huggingface.co/docs/datasets/loading.
Besides that, there's the dataset viewer which allows people to quickly explore the data samples in the browser.
After uploaded, we can also link the dataset to the paper page so people can discover your work more easily.
Let me know if you're interested or need any guidance!
Kind regards,
Niels
Hi @indulgeBai 馃
I'm Niels and work as part of the open-source team at Hugging Face. I discovered your work through Papers with Code as yours got featured: https://paperswithcode.co/paper/2606.17800.
The paper page lets people discuss about your paper and lets them find artifacts about it (your models for instance), you can also claim the paper as yours which will show up on your public profile at HF, add Github and project page URLs.
It's great to see that you've already set up the model repository for MaineCoon on the Hub!
Would you also like to host the SocialVideo-Bench dataset you've introduced on https://huggingface.co/datasets?
Hosting the benchmark on Hugging Face will give it more visibility and enable better discoverability within the research community. It will also allow people to easily use the benchmark via the library:
If you're interested, you can find a guide for uploading datasets here: https://huggingface.co/docs/datasets/loading.
Besides that, there's the dataset viewer which allows people to quickly explore the data samples in the browser.
After uploaded, we can also link the dataset to the paper page so people can discover your work more easily.
Let me know if you're interested or need any guidance!
Kind regards,
Niels